1. The Field of the Invention
This invention generally relates to facilitating communication between a clinical system and a separate expert system. More specifically, the present invention relates to systems, methods, and computer programs that provide an interface between a clinical system and a separate expert system.
2. The Relevant Technology
Clinical information systems and electronic medical records systems have been used in patient care for many years. These systems contain a database or repository of data related to the users and administrative functions of the system, as well as a history of clinical results and activities (clinical data functions). They are used as a medical record, for financial transactions related to care, and as a tool for the ongoing clinical treatment of the patient. However, historically, these systems have been built as Online Transaction Processing (OLTP) systems. As a result, they do not contain a great deal of medical or scientific knowledge, and are not designed to provide expert recommendations, (i.e. perform expert functions).
Some clinical information systems have been built with alerting mechanisms and rule-based event monitors embedded within them to provide expert recommendations based on clinical data entered in the system. These systems do not require specific system interfaces between different modules performing the clinical data functions and the expert functions because the clinical data functions and expert functions are embodied in a common system. The need for rapid processing of transactions has limited the power of this model, and in turn has limited the type of expert advice which can be generated. In addition, a user is limited to the features provided by the specific expert system embedded within the common system that has been developed or purchased. There is no opportunity to combine a different expert system within the clinical system itself.
Online Analytic Processing Systems have been developed to provide optimal analytic expert functions. However, these are separate from clinical systems, and while they may have inbound data connection from clinical systems to populate their databases, there is no flow of information back to the clinical system, nor is there an interactive mechanism between the two systems which allows users to move seamlessly between the two types of functionality. These systems are generally used for administrative or case management purposes, rather than direct clinical care. The knowledge embedded and the recommendations made are not directly actionable.
Expert systems have been developed as stand-alone systems, and have been shown to provide valuable information that has the potential to improve medical care. However, their separate nature has limited their usefulness as well. Systems that require the user to enter a separate application are less likely to be used, and those that require the user to enter clinical information that already resides in clinical systems place an additional burden on the user. In addition, they risk loss of data fidelity (or accuracy) because reentered data may be incomplete or in error. The separate nature of these stand-alone systems has thus limited their usefulness and their adoption in clinical practice.
Stand-alone expert systems have not been integrated into clinical systems for a number of reasons. First, comprehensive Electronic Medical Record (EMR) systems are found in very few health systems. Those few sites that have such Electronic Medical Record systems have often developed them in house, and have developed decision support and expert systems within the Electronic Medical Record system itself.
Separate expert systems have been developed for a number of focused clinical areas, but without an Electronic Medical Record system in place, integration was not possible. In addition, there are many technical barriers to an integrated system. First, many Electronic Medical Records have been developed with proprietary operating systems and databases. These systems are difficult if not impossible to integrate with unrelated systems. Second, there is a lack of standards for data and knowledge representation. This makes it difficult to transfer data that could be properly interpreted and manipulated. Even with interface standards that define the structure of messages between systems, the content of the messages may be useless without a common vocabulary.
Commercial systems have also not been developed which integrate stand-alone expert systems with clinical Electronic Medical Records. The business model of Electronic Medical Record vendors is to provide comprehensive solutions to health systems. They differentiate themselves by virtue of the functionality in their expert systems. These systems are integral to their products, and they are not developed to work with the Electronic Medical Record of another vendor. This has discouraged development of independent expert systems that are designed to integrate broadly. Vendors of small niche expert systems have focused on specific areas of functionality such as case management, insurance certification of appropriateness of care, and data analysis. Direct care clinicians do not generally use these systems, and so integration with the Electronic Medical Record has not been pursued.
Finally, the conventional wisdom and teaching of the medical informatics literature has discouraged separate expert systems. Because of the problems with performance, security, vocabulary inconsistencies, and control over development, the widely stated belief has been that expert systems can only be effective when they are built directly into clinical systems. The result of this teaching has been to encourage the development of expert systems that are built into clinical systems, and no attention has been paid to developing a system or method to permit an independent expert system to function in an integrated fashion.